Rez Dog Blues & The Haiku — with William Lindsay
Bibliographic record
Abstract
William Lindsay worked as an educator at Simon Fraser University, the University of British Columbia, and Concordia University. In this episode, Am and William discuss the writing process for his latest book, “Rez Dog Blues & The Haiku: A Savage Life in Bits and Pieces,” and its focus on music and movies, horror and hope, and the honest depiction of Indigneous life, in the 60s and 70s, on reserve and then in the Downtown Eastside of Vancouver.\nContent Warning:The stories in this series deal with difficult and sometimes traumatic topics. Please practice self care, stop listening and seek support if you need to. Help is available!\nMental Health Support:\nCrisis Centre BC: crisiscentre.bc.ca/\nIndian Residential School Survivors Society: www.irsss.ca/services\nKUU-US Crisis Line: www.kuu-uscrisisline.com/\nWAVAW Rape Crisis Centre: www.wavaw.ca/\nBC Mental Health and Substance Use Services: www.bcmhsus.ca/
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.050 | 0.018 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".